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24th International Conference on Computational science (ICCS)

作者： Fertin, Guillaume Monfroy, Eric Vasconcellos-Gaete, Claudia Nantes Univ Ecole Cent Nantes CNRS LS2NUMR 6004 F-44000 Nantes France Univ Angers LERIA Angers France

ISBN: (纸本)9783031637742;9783031637759

Given an optimization problem, combining knowledge from both (i) structural or algorithmic known results and (ii) new solving techniques, helps gain insight and knowledge on the aforementioned problem by tightening the gap between lower and upper bounds on the sought optimal value. Additionally, this gain may be further improved by iterating (i) and (ii) until a fixed point is reached. In this paper, we illustrate the above through the classical Cyclic Bandwidth problem, an optimization problem which takes as input an undirected graph G = (V, E) with |V| = n, and asks for a labeling. of V in which every vertex v takes a unique value phi(v) is an element of [1;n], in such a way that B-c(G, phi) = max{min(uv)is an element of E(G){|phi(u)-phi(v)|, n-|phi(u)-phi(v)|}}, called the cyclic bandwidth of G, is minimized. Using the classic benchmark from the Harwell-Boeing sparse matrix collection introduced in [16], we show how to combine (i) previous results from the Cyclic Bandwidth literature, and (ii) new solving techniques, which we first present, and then implement, starting from the best results obtained in step (i). We show that this process allows us to determine the optimal cyclic bandwidth value for half of the instances of our benchmark, and improves the best known bounds for a large number of the remaining instances.

关键词： Graph Labeling Cyclic Bandwidth Lower Bounds Upper Bounds Constraint programming Solver

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An Undergraduate Course on computer Architecture 56

An Undergraduate Course on Computer Architecture

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56th Annual SIGCSE Technical Symposium on computer science Education, SIGCSE TS 2025

作者： Nowak, Przemyslaw Puchala, Dariusz Stokfiszewski, Kamil Institute of Information Technology Lodz University of Technology Lodz Poland

ISBN: (纸本)9798400705328

Teaching computer architecture to students focused on high-level programming is a challenging task. Such students often struggle with the complexities of this subject, exhibiting difficulties in grasping connections between hardware and software and in understanding low-level concepts. Here, we present the curriculum for an undergraduate course on computer architecture, which combines lectures and practical assignments, covering the main hardware components of the computer system and their interactions. Our description focuses on the practical assignments, of which the first one introduces basic assembly programming, the second one concerns communication with peripheral devices using ports and memory mapping, the third one deals with the interrupt system and the real-time clock, and the last one is related to how the graphics card operates in a graphics mode. We also report that students' engagement can be increased if the assignments involve programming in a high-level language such as C equipped with a library offering low-level instructions instead of assembly language. © 2025 Copyright held by the owner/author(s).

关键词： computer architecture cs1 low-level programming undergraduate course

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A novel implicit FEM-MPM coupling framework using convex cone programming for elastoplastic problems

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computer METHODS IN APPLIED MECHANICS AND ENGINEERING 2024年 429卷

作者： Zhou, Xi -Wen Jin, Yin -Fu He, Kai -Yuan Yin, Zhen-Yu Liu, Feng- Tao Shenzhen Univ State Key Lab Intelligent Geotech & Tunnelling Shenzhen 518060 Guangdong Peoples R China Shenzhen Univ Natl Engn Res Ctr Deep Shaft Construct Shenzhen 518060 Guangdong Peoples R China Shenzhen Univ Coll Civil & Transportat Engn Shenzhen 518060 Guangdong Peoples R China Hong Kong Polytech Univ Dept Civil & Environm Engn Kowloon Hong Kong Peoples R China Guilin Univ Technol Sch Civil Engn & Architecture Guilin 541004 Peoples R China

Most existing Finite Element Method and the Material Point Method (FEM-MPM) coupling is designed for explicit solvers. By contrast, implicit schemes offer the advantage of substantially larger time steps while maintaining enhanced stability, particularly beneficial for tackling stiff nonlinear problems. Despite this, the development of implicit FEM-MPM coupling has not been extensively explored, leaving a notable gap in the context of contact and elastoplastic deformation challenges. Thus, this paper proposes a novel unified FEM-MPM coupling approach within implicit time integration under the framework of multivariable variational principle and convex cone programming, termed CP-FEMP. The CP-FEMP is the first successful attempt to impose the contact constraints via Lagrange multiplier and barrier method under convex cone programming, which can tackle not only the tie constraints but also the frictional contact between MPM and FEM domains with ensuring convergence and feasibility regardless of the time step size or the mesh resolutions. The contact locking issue in tie contact is circumvented using a well-defined interpolation space. The governing equations, associated frictional contact model, and associated elastoplastic constitutive law are formulated into a global convex optimisation problem, which is efficiently solved using primal-dual interior-point method. Through a succession of standard contact and elastoplastic benchmarks, the CP-FEMP demonstrates its proficiency in the precise transference of contact forces across MPM and FEM domains while showcasing commendable energy conservation attributes. Finally, the CP-FEMP is applied to a slope-retaining wall interaction problem. All results demonstrate CP-FEMP provides a comprehensive solution for FEM-MPM coupling, allowing for large incremental step under nonlinear contact , elastoplastic large deformation and guaranteeing strict, hard non -penetration conditions without convergence issues.

关键词： Implicit time integration FEM-MPM coupling Elastoplastic deformation Tie contact Frictional contact Convex cone programming

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Uncovering the skillsets required in computer science jobs using social network analysis

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EDUCATION AND INFORMATION TECHNOLOGIES 2024年第10期29卷 12759-12780页

作者： Maghsoudi, Mehrdad Shahid Beheshti Univ Fac Management & Accounting Dept Ind & Informat Management Tehran Iran

The rapid growth of technology and computer science, which has led to a surge in demand for skilled professionals in this field. The skill set required for computer science jobs has evolved rapidly, creating challenges for those already in the workforce who need to adapt their skills quickly to meet industry demands. To stay ahead of the curve, it is essential to understand the hottest skills needed in the field. The article introduces a new method for analyzing job advertisements using social network analysis to identify the most critical skills required by employers in the *** this research, to form the communication network of skills, first 5763 skills were collected from the LinkedIn social network, then the relationship between skills was collected and searched in 7777 computer science job advertisements, and finally, the balanced communication network of skills was formed. The study analyzes the formed communication network of skills in the computer science job market and identifies four distinct communities of skills: Generalists, Infrastructure and Security, Software Development, and Embedded Systems. The findings reveal that employers value both hard and soft skills, such as programming languages and teamwork. Communication skills were found to be the most important skill in the labor market. Additionally, certain skills were highlighted based on their centrality indices, including communication, English, SQL, Git, and business skills, among others. The study provides valuable insights into the current state of the computer science job market and can help guide individuals and organizations in making informed decisions about skills acquisition and hiring practices.

关键词： computer science Jobs Skillsets Required Hard and Soft Skills Social Network Analysis Community analysis

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Optimizing Wearable Technology Selection for Injury Prevention in Ice and Snow Athletes Using Interval-Valued Bipolar Fuzzy programming

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INTERNATIONAL JOURNAL OF ADVANCED computer science AND APPLICATIONS 2024年第11期15卷 1156-1163页

作者： Li, Aichen Jilin Inst Chem Technol Dept Phys Educ Jilin 132022 Peoples R China

The growing importance of wearable technology in ice and snow sports highlights its role in injury prevention, where environmental hazards elevate injury risks. To address this, we propose a decision-making model using interval-valued bipolar fuzzy programming (IVBFP) for the optimal selection of wearable devices focused on athlete safety. The model employs multi-criteria decision-making (MCDM) methods to evaluate critical factors such as comfort, safety, durability, and real-time monitoring. Fuzzy logic enhances the precision and consistency of decision-making. The IVBFP model addresses vital challenges, including the diverse performance metrics of wearable devices and the uncertainty in expert evaluations. In comparison analyses, the model exhibited a 15% enhancement in judgment accuracy and a 12% decrease in uncertainty relative to conventional techniques. The results underscore the model's proficiency in correctly forecasting devices that mitigate injury risks, providing improved athlete protection. The approach effectively incorporates expert viewpoints and subjective evaluations, diminishing harm risk in simulated and actual datasets. This research is significant both theoretically and practically. It offers a comprehensive framework to guarantee athlete safety in extreme conditions, connecting scholars and practitioners.

关键词： Wearable technology injury prevention Interval-Valued Bipolar Fuzzy programming (IVBFP) Multi-Criteria Decision-Making (MCDM) fuzzy logic real-time monitoring

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Local Spaces in Soft Concurrent Constraint programming Oriented to Security 12th

Local Spaces in Soft Concurrent Constraint Programming Orien...

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12th International Symposium on Leveraging Applications of Formal Methods, Verification and Validation

作者： Bistarelli, Stefano Santini, Francesco Univ Perugia Dipartimento Matemat & Informat Perugia Italy

ISBN: (纸本)9783031737084;9783031737091

Concurrent Constraint programming (CCP) originated in the late '80s with Vijay A. Saraswat's work. In the first '00s, a "soft" perspective of the constraint store based on a parametric algebraic structure (a c-semiring) was proposed, namely soft CCP (SCCP). This paper enhances this SCCP language with local constraint spaces, where agents can see and interact with only a portion of the information stored. Thus, it is possible to represent areas where an agent can perform operations without affecting other local spaces. The resulting language is security-oriented as actions are checked against (e.g., read/write) rights, and it is quite rich because of nonmonotonic operations in the store (e.g., the removal of constraints is allowed), thus making the coordination of several agents more flexible and adaptive to personal and global goals.

关键词： Soft CCP Local Space Functions Security

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A genetic programming approach with adaptive region detection to skin cancer image classification

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Journal of Automation and Intelligence 2024年第4期3卷 240-249页

作者： Kunjie Yu Jintao Lian Ying Bi Jing Liang Bing Xue Mengjie Zhang School of Electrical and Information Engineering Zhengzhou UniversityZhengzhou450001China State Key Laboratory of Intelligent Agricultural Power Equipment Luoyang471000China Longmen Laboratory Luoyang471000China School of Electrical Engineering and Automation Henan Institute of TechnologyXinxiang453000China School of Engineering and Computer Science&Centre for Data Science and Artificial Intelligence Victoria University of WellingtonWellington6201New Zealand

Dermatologists typically require extensive experience to accurately classify skin *** recent years,the development of computer vision and machine learning has provided new methods for assisted *** skin cancer image classification methods have certain limitations,such as poor interpretability,the requirement of domain knowledge for feature extraction,and the neglect of lesion area information in skin *** paper proposes a new genetic programming(GP)approach to automatically learn global and/or local features from skin images for *** achieve this,a new function set and a new terminal set have been *** proposed GP method can automatically and flexibly extract effective local/global features from different types of input images,thus providing a comprehensive description of skin images.A new region detection function has been developed to select the lesion areas from skin images for feature *** performance of this approach is evaluated on three skin cancer image classification tasks,and compared with three GP methods and six non-GP *** experimental results show that the new approach achieves significantly better or similar performance in most *** analysis validates the effectiveness of our parameter settings,visualizes the multiple region detection functions used in the individual evolved by the proposed approach,and demonstrates its good convergence ability.

关键词： Genetic programming Skin cancer image classification Region detection Feature extraction

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ITiCSE 2024 - Proceedings of the 2024 Conference Innovation and Technology in computer science Education

ITiCSE 2024 - Proceedings of the 2024 Conference Innovation ...

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29th Conference Innovation and Technology in computer science Education, ITiCSE 2024

ISBN: (纸本)9798400706035

The proceedings contain 171 papers. The topics discussed include: teaching programming in the age of generative AI;early adoption of generative artificial intelligence in computing education: emergent student use cases and perspectives in 2023;guidelines for the evolving role of generative ai in introductory programming based on emerging practice;AI-grading standup updates to improve project-based learning outcomes;artificial intelligence in everyday life 2.0: educating university students from different majors;in-person vs blended learning: an examination of grades, attendance, peer support, competitiveness, and belonging;on using physiological sensors and ai to monitor emotions in a bug-hunting game;fostering and assessing dispositions by providing grades a meaning in a computing education context;ordered network analysis in CS education: unveiling patterns of success and struggle in automated programming assessment;and with great power comes great responsibility - integrating data ethics into computing education.

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Detecting Learning Behavior in programming Assignments by Analyzing Versioned Repositories

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IEEE ACCESS 2024年 12卷 188828-188844页

作者： Chen, John Lau, Serena Leinonen, Juho Terragni, Valerio Giacaman, Nasser Univ Auckland Dept Elect Comp & Software Engn Auckland 1010 New Zealand Aalto Univ Dept Comp Sci Espoo 02150 Finland

Computing education plays a significant role in shaping the calibre of future computing professionals;hence, improving its quality is a valuable endeavour. A promising approach to enhance computing education is leveraging student data from version control systems (VCS). While previous studies have utilised VCS data to predict academic performance, there remains a gap in harnessing this data for learning analytics to understand student learning behaviours in real time. In this research, we introduce the Polivr ecosystem, a comprehensive platform designed to address this gap by utilising VCS data for learning analytics in computing education. The Polivr ecosystem comprises three key modules: Polivr Anonymiser, which ensures data privacy by anonymising student identities;Polivr Core, which mines learning metrics from Git repositories;and Polivr Web Viewer, which transforms the raw metrics into insightful visualisations for educators. We evaluated Polivr using anonymised repositories collected from undergraduate computing courses. The resulting visualisations revealed trends and patterns in student learning behaviours, such as coding habits and progression over time. These insights provide valuable information for educators to enhance teaching strategies and potentially identify at-risk students. This research demonstrates the potential of version control systems as a rich source of learning analytics, contributing to improving computing education by enabling data-driven decision-making in instructional design and student support.

关键词： Measurement Data mining Education programming profession Ethics Data visualization Control systems Computational modeling Software measurement Predictive models Computing education Git learning analytics learning behaviour mining software repositories version control

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Propagation and Masking Characteristics of Errors During Software Testing in Synchronous programming

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IEEE ACCESS 2024年 12卷 146009-146021页

作者： Kim, Young-Mi Choi, Jin-Young Yoo, Seunghoon Park, Myunghwan Korea Univ Dept Comp & Radio Commun Engn Seoul 02841 South Korea Korea Univ Sch Cybersecur Seoul 02841 South Korea Republ Korea Air Force Acad Dept Comp Sci Cheongju 28187 South Korea

During testing, an error in software can either propagate to the output variables or be masked before it reaches them. Error propagation and masking characteristics are crucial in software testing because they directly influence testing effectiveness. The testing community has hence focused on developing test mechanisms to promote the propagation and reduce masking of errors in software under test. However, little is known about how severely the errors propagate and are masked during software execution. Moreover, little is known about what influences software's propagation and masking characteristics. Thus, in this study, we performed experiments to investigate the behavior of errors during software execution. We chose six case examples and created mutants per case example by seeding an error into each one. We then executed the mutants with randomly selected test cases and investigated how many errors were propagated and masked. If an error was masked, we examined the cause. In addition, we investigated what percentage of errors in the mutants reached the output variables. This study provides insight into the characteristics of errors in terms of propagation and masking, which will help testers design test inputs and choose monitoring variables to properly handle the masking of errors during testing.

关键词： Software Testing Measurement uncertainty programming Monitoring Software measurement computer languages Software testing Java Sensitivity analysis Error masking error propagation synchronous programming Lustre language mutant generation test cases

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